Flood inundation mapping in the Kelantan River Basin, Malaysia, using Sentinel-1 SAR and Google Earth Engine

One of the most severe floods in Peninsular Malaysia occurred during 2021-2022, displacing over 20,000 people and resulting in two deaths in Kelantan. Accurate flood extent data during such events is crucial for effective flood management, however, gathering this information is challenging due to limited access to affected area. Google Earth Engine (GEE) offers rapid satellite image processing for flood inundation mapping, making it an effective tool for this purpose. In this study, GEE was utilized to generate flood inundation maps for the Kelantan River Basin (KRB) using Sentinel-1 SAR data. Site inspections and Sentinel-2 Multispectral Instrument (MSI) satellite images of the actual flood regions were then used to validate the flood inundation maps. Additionally, this study evaluated the effects of three distance thresholds (3-, 4- and 5-pixel) to differentiate inundated area from preliminary water surfaces. The findings showed that the flood inundation maps achieved an accuracy of 57 – 60%, with the highest accuracy observed under the 5-pixel threshold. The 2021-2022 flood, with an inundated area of 8.92 km 2 , was one of the worst experiences in Kota Bharu. These findings provide valuable insights to support local authorities in designing better flood mitigation strategies for the future. Keywords: Climate change, climate extreme, flood GEE, Kelantan, Sentinel-1

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Publication Details

Journal
Malaysian Journal of Society and Space
Published
2024-11-29
DOI
https://doi.org/10.17576/geo-2024-2004-02
Primary Topic
Flood Risk Assessment and Management
Type
article
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article

Flood inundation mapping in the Kelantan River Basin, Malaysia, using Sentinel-1 SAR and Google Earth Engine

Mou Leong Tan, Longhui Li, Yi Lin Tew, Mohamad Hafiz Hassan et al.
Malaysian Journal of Society and Space
Flood Risk Assessment and Management
article

Flood inundation mapping in the Kelantan River Basin, Malaysia, using Sentinel-1 SAR and Google Earth Engine

Mou Leong Tan, Longhui Li, Yi Lin Tew, Mohamad Hafiz Hassan, Sazali Osman, Narimah Samat, Liew Juneng, Chun Kiat Chang
article en

Abstract

One of the most severe floods in Peninsular Malaysia occurred during 2021-2022, displacing over 20,000 people and resulting in two deaths in Kelantan. Accurate flood extent data during such events is crucial for effective flood management, however, gathering this information is challenging due to limited access to affected area. Google Earth Engine (GEE) offers rapid satellite image processing for flood inundation mapping, making it an effective tool for this purpose. In this study, GEE was utilized to generate flood inundation maps for the Kelantan River Basin (KRB) using Sentinel-1 SAR data. Site inspections and Sentinel-2 Multispectral Instrument (MSI) satellite images of the actual flood regions were then used to validate the flood inundation maps. Additionally, this study evaluated the effects of three distance thresholds (3-, 4- and 5-pixel) to differentiate inundated area from preliminary water surfaces. The findings showed that the flood inundation maps achieved an accuracy of 57 – 60%, with the highest accuracy observed under the 5-pixel threshold. The 2021-2022 flood, with an inundated area of 8.92 km 2 , was one of the worst experiences in Kota Bharu. These findings provide valuable insights to support local authorities in designing better flood mitigation strategies for the future. Keywords: Climate change, climate extreme, flood GEE, Kelantan, Sentinel-1

Malaysian Journal of Society and SpaceVol. 20(4)
Universiti Sains Malaysia (MY), Nanjing Normal University (CN), National University of Malaysia (MY)
Climate action
Openalex Percentile: Top 81%
Flood Risk Assessment and Management
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